Update app.py

app.py

@@ -2,86 +2,77 @@ import gradio as gr
 import cv2
 import random
 import os
-from services.video_service import get_random_video_frame
 from services.detection_service import detect_objects
 from services.thermal_service import detect_thermal_anomalies
-from services.shadow_detection import detect_shadow_coverage
-from services.salesforce_dispatcher import send_to_salesforce
+from services.video_service import get_random_video_frame
 
-# Initialize counters
-frame_counter = 0
-intrusion_counter = 0
-thermal_counter = 0
-shadow_issue_counter = 0
+# Paths
+TEMP_IMAGE_PATH = "temp.jpg"
 
-# Random frame generator
-frame_gen = get_random_video_frame()
+# Initialize Metrics
+total_frames = 0
+total_detections = 0
+total_anomalies = 0
 
-# Metrics state updater
 def monitor_feed():
-    global frame_counter, intrusion_counter, thermal_counter, shadow_issue_counter
-
-    try:
-        frame, current_video = next(frame_gen)
-
-        temp_path = "temp.jpg"
-        cv2.imwrite(temp_path, frame)
-
-        detections = detect_objects(temp_path)
-        thermal_boxes = detect_thermal_anomalies(temp_path)
-        shadow_flag = detect_shadow_coverage(temp_path)
-
-        frame_counter += 1
-        intrusion_detected = any(d['label'] == 'person' for d in detections)
-
-        if intrusion_detected:
-            intrusion_counter += 1
+    global total_frames, total_detections, total_anomalies
+
+    frame = get_random_video_frame()
+
+    if frame is None:
+        return None, None, None
+
+    # Save frame temporarily
+    cv2.imwrite(TEMP_IMAGE_PATH, frame)
+
+    # Object detection
+    detections = detect_objects(TEMP_IMAGE_PATH)
+    detection_boxes = []
+    if detections:
+        for det in detections:
+            box = det['box']
+            label = det['label']
+            detection_boxes.append(label)
+            x, y, w, h = box
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+            cv2.putText(frame, label, (x, y - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+    # Thermal detection
+    anomalies = detect_thermal_anomalies(TEMP_IMAGE_PATH)
+    anomaly_labels = []
+    if anomalies:
+        for anomaly in anomalies:
+            label = anomaly['label']
+            anomaly_labels.append(label)
+
+    # Update metrics
+    total_frames += 1
+    total_detections += len(detection_boxes)
+    total_anomalies += len(anomaly_labels)
+
+    # Overlay live metrics
+    metrics_text = f"Frames: {total_frames} | Detections: {total_detections} | Anomalies: {total_anomalies}"
+    cv2.putText(frame, metrics_text, (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)
+
+    return frame, {"Detections": detection_boxes}, {"Thermal Anomalies": anomaly_labels}
 
-        if thermal_boxes:
-            thermal_counter += 1
-
-        if shadow_flag:
-            shadow_issue_counter += 1
-
-        # Commented Salesforce Push (can enable later)
-        # alert_payload = {
-        #     "detections": detections,
-        #     "thermal": bool(thermal_boxes),
-        #     "shadow_issue": shadow_flag,
-        # }
-        # send_to_salesforce(alert_payload)
-
-        return frame, frame_counter, intrusion_counter, thermal_counter, shadow_issue_counter, current_video
-
-    except StopIteration:
-        return None, frame_counter, intrusion_counter, thermal_counter, shadow_issue_counter, "End of Video"
-
-
-# Gradio Blocks UI
 def build_interface():
-    with gr.Blocks(title="Solar Surveillance Feed Simulation with Live Metrics") as app:
+    with gr.Blocks() as demo:
+        gr.Markdown("# Solar Surveillance System \U0001F310\U0001F50D")
         with gr.Row():
             with gr.Column(scale=3):
-                video_display = gr.Image(label="Surveillance Feed", show_label=True)
-
+                image_output = gr.Image(label="Live Video Feed")
             with gr.Column(scale=1):
-                gr.Markdown("## 📊 Live Metrics")
-                frame_count_display = gr.Number(label="Frames Processed", interactive=False)
-                intrusion_count_display = gr.Number(label="Intrusions Detected", interactive=False)
-                thermal_count_display = gr.Number(label="Thermal Hotspots", interactive=False)
-                shadow_count_display = gr.Number(label="Shadow Issues", interactive=False)
-                current_video_display = gr.Textbox(label="Current Video", interactive=False)
+                detection_json = gr.JSON(label="Detections")
+                thermal_json = gr.JSON(label="Thermal Anomalies")
+                gr.Markdown("**Live Metrics Auto Updating** \U0001F4CA")
 
-        app.load(
-            monitor_feed,
-            inputs=[],
-            outputs=[video_display, frame_count_display, intrusion_count_display, thermal_count_display, shadow_count_display, current_video_display],
-            every=1.0  # seconds
-        )
-    return app
+        demo_btn = gr.Button("Start Monitoring")
+        demo_btn.click(fn=monitor_feed, outputs=[image_output, detection_json, thermal_json])
 
+    return demo
 
-# Launch the app
 if __name__ == "__main__":
     demo = build_interface()
+    demo.queue()
     demo.launch()